Instructions to use matgu23/cntblv with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Diffusers
How to use matgu23/cntblv with Diffusers:
pip install -U diffusers transformers accelerate
import torch from diffusers import DiffusionPipeline # switch to "mps" for apple devices pipe = DiffusionPipeline.from_pretrained("matgu23/cntblv", dtype=torch.bfloat16, device_map="cuda") prompt = "Astronaut in a jungle, cold color palette, muted colors, detailed, 8k" image = pipe(prompt).images[0] - Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- Draw Things
- DiffusionBee
- Xet hash:
- d1065ca8e97fe8ee540389b12a9d2c96ad4c46f7e0af8841babe8557fa8592ef
- Size of remote file:
- 246 MB
- SHA256:
- bf69c3680c053d684d28227f6a89a195ca4f02c2bfb9f1b80ea36785a88fd539
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